The function of an optronic surveillance system is to detect and follow targets entering a surveillance zone.
The crucial problem of detecting a target (or object) in a video sequence is to find a criterion designated the “detection criterion” which makes it possible to decide, for each image comprising pixels, which are the pixels of a target. The choice of this criterion leads to detection performance defined as a function of the probability of detection—probability of false alarm pair.
Note that the probability of detection is the probability for a pixel of a target (or of a threatening object) to be declared a target; the probability of false alarm is the probability for a pixel of a non-threatening object to be declared a target.
In surveillance systems for airborne targets, images acquired in the infrared wavelengths are generally used. They they provide a good detection criterion since most of the targets are propelled and therefore supply a high IR signal.
For a long-range air to air surveillance system, detection consists in distinguishing, with a high probability of detection and a low probability of false alarm, a pixel that can exhibit a low signal-to-noise ratio (SNR),), that is a pixel which signal is weak compared to the signals of its background pixels.
The main sources of false alarms are:                noise samples on the background pixels of the target which produce an additional signal that is comparable in certain cases with that of a target,        artifacts varying rapidly in the background which produce a very strong signal (reflections of the sun on the edge of the clouds for example).        
The systems considered are more particularly the low-frequency scanning surveillance systems operating with a high-frequency acquisition device.
FIG. 1 illustrates an example of a known surveillance system comprising scanning means making it possible to analyze preferably repetitively a sector S of space. This system comprises an “a×b” instantaneous-field front optical system 1 and scanning means 2 allowing the sector S to be observed with a given “A×B” total field. The scanning means are controlled by a processing unit allowing the sector to be scanned. The surveillance system also comprises means for forming an image 3 on the pixels of the matrix detector 41 included in the detection means 4. This involves the image of a scene situated in a given “a×b” field zone, situated in the sector S. The system may also comprise backscanning means 6 making it possible to compensate for the movements of the image due to the scanning of the scene during the acquisition of the images. For example, the processing unit 5 can synchronize the acquisition of the images with the scanning by backscanning means.
On these systems, the matrix detector 41 covers a band of space (which dimension is “a×b”) by rotation of the scanning means 2. In this case, a point of the sector S is not observed permanently, but over a period which duration depends on the time spent to return to this point after having scanned the whole of the sector S. Backscanning means 6 make it possible, on the one hand, to ensure the stability of the line of view during the integration time of the matrix detector 41 for each image, and, on the other hand, to observe the same “a×b” zone of space (with a dimension substantially equal to the instantaneous field of the matrix detector 41, or possibly less than the latter) so long as the means 2 for scanning the sector do not require the move to the next zone. Usually, the scanning/backscanning means 2, 6 provide a certain overlap between two consecutive observed zones in order to eliminate the risk of forming ‘blind’ zones due to errors in the mechanisms, and in order to handle without additional difficulty the case of targets which move in the reference frame of the matrix detector.
Depending on the frequency of acquisition of the images and the velocity of rotation of the scanning means, a certain number of images of the same zone is therefore obtained (with the same direction of view).
These surveillance systems are characterized by:                a significant delay (which may be as long as several seconds) between two consecutive observations of the same zone when there are two successive analyses of the sector S,        a large number N (of the order of several tens) of acquisitions of images of the same object (or target) of a scene on each scan: N consecutive images then include the same object.        
This method has been illustrated in FIG. 2 with the following values:                The sector S of a field represented by an angle A×B is scanned over its width A in T seconds, namely at an angular velocity θ′, for example 20° in 2 s, namely θ′=A/T=10° s−1.        
Let a be the angular width of the instantaneous field of the matrix detector; the time dedicated to the acquisition of the images of a scene covering an angular width “a” is equal to the time necessary to scan this width at the angular velocity θ′, namely t=a/θ′, for example for a=1° and θ′=10° s−1, t=0.1 s.
The term “angular width” is not limited to an orientation in space.
Let f be the sampling rate of the matrix detector (image rate), for example f=400 Hz, namely a sampling period te=1/f=2.5 ms.
Then the number N of images dedicated to this same angular zone is equal to N=t/te=a f/θ′, namely N=40.
In the figure, and in order not to overload it, a point object O is therefore present in 40 consecutive images, numbered from n to n+39. This object is not present in the previous 40 images (numbered from n−40 to n−1) or in the next 40 images (numbered from n+40 to n+79).
The problem is to optimize the use of these N images in order to detect the object with a high probability of detection and to as much as possible eliminate false alarms due notably to artifacts.